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Keyword spotting based on the analysis of template matching distances
Faculty of Informatics - Papers (Archive)
  • Mohamed Barakat, University of Wollongong
  • Christian H Ritz, University of Wollongong
  • David A Stirling, University of Wollongong
RIS ID
52732
Publication Date
1-1-2011
Publication Details

M. S. Barakat, C. H. Ritz & D. A. Stirling, "Keyword spotting based on the analysis of template matching distances," in 5th International Conference on Signal Processing and Telecommunication Systems, ICSPCS'2011, 2011, pp. 1-6.

Abstract

This paper presents a system for speakerindependent keyword spotting (KWS) in continuous speech usinga spoken example template. The approach, based on DynamicTime Warping (DTW) for matching the template to a testutterance, does not require any modelling or training as requiredin alternative techniques such as the Hidden Markov Model(HMM). This is of particular relevance to applications such asdetection of words that have not been adequately represented ina training database (e.g. searching for topical words that areemerging in society). Introduced is the use of the DTW distancehistogram for automatic estimation of similarity thresholds forevery keyword-utterance pair. Experiments conducted on a widerange of speech sentences and keywords show that when only afew examples of the keyword are available, the proposed systemhas higher recall ratio than a HMM-based approach.

Citation Information
Mohamed Barakat, Christian H Ritz and David A Stirling. "Keyword spotting based on the analysis of template matching distances" (2011) p. 1 - 6
Available at: http://works.bepress.com/dstirling/1/